erwin

APRIL 2, 2021

Organizations are managing more data than ever. With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Who is authorized to use it and how?

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

erwin

OCTOBER 31, 2019

Do you know where your data is? What data you have? Add to the mix the potential for a data breach followed by non-compliance, reputational damage and financial penalties and a real horror story could unfold. s Information Commissioner’s Office had levied against both Facebook and Equifax for their data breaches.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

In(tegrate) the Clouds

JUNE 23, 2016

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses. Integration is event-based rather than clock-driven.

Data Integration 49

Data Integration Data Lake Data Warehouse Data-driven 49

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 79

Data Lake Data Warehouse Data-driven Optimization 79

AWS Big Data

MARCH 20, 2024

As your organization becomes more data driven and uses data as a source of competitive advantage, you’ll want to run analytics on your data to better understand your core business drivers to grow sales, reduce costs, and optimize your business. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 122

Data Warehouse Business Driver Data Lake Data-driven 122

AWS Big Data

MAY 16, 2024

In this post, we discuss how Amazon Redshift spatial index functions such as Hexagonal hierarchical geospatial indexing system (or H3) can be used to represent spatial data using H3 indexing for fast spatial lookups at scale. Navigating the vast landscape of data-driven insights has always been an exciting endeavor.

Data Warehouse 108

Data Warehouse Visualization Cost-Benefit Optimization 108

BI-Survey

AUGUST 21, 2020

Data warehousing is getting on in years. However, data warehousing and BI applications are only considered moderately successful. Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. Can the basic nature of the data be proactively improved?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

Cloudera

AUGUST 30, 2022

Data is the fuel that drives government, enables transparency, and powers citizen services. It outlines a scenario in which “recently married people might want to change their names on their driver’s licenses or other documentation. Data quality issues deter trust and hinder accurate analytics. Modern data architectures.

Data Architecture 79

Data Architecture Data Lake Metadata Data Warehouse 79

Cloudera

OCTOBER 7, 2022

dbt allows data teams to produce trusted data sets for reporting, ML modeling, and operational workflows using SQL, with a simple workflow that follows software engineering best practices like modularity, portability, and continuous integration/continuous development (CI/CD). The Open Data Lakehouse . Introduction.

Data Warehouse 81

Data Warehouse Data Transformation Testing Data Lake 81

Cloudera

AUGUST 9, 2022

The previous decade has seen explosive growth in the integration of data and data-driven insight into a company’s ability to operate effectively, yielding an ever-growing competitive advantage to those that do it well. Data is integral for both long-term strategy and day-to-day, or even minute-to-minute operation.

Data Lake 78

Data Lake Data Warehouse Data-driven IoT 78

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 75

Data Quality Data Lake Data-driven Metrics 75

CIO Business Intelligence

JUNE 6, 2023

Distributed data ownership is a new idea that has recently captured the attention of IT executives and chief data officers. The concept: data should be curated by the people who know it best versus locked up in an IT ivory tower. Ultimately, data served as a product may be used by anyone in the organization.

Management 52

Management Data Warehouse Data Lake Digital Transformation 52

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks. Greg Rahn: Sure.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 96

Analytics Visualization Data Integration Cost-Benefit 96

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. The last 10+ years or so have seen Insurance become as data-driven as any vertical industry.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Ontotext

FEBRUARY 26, 2024

The goal: a data-driven organization Let’s zoom out for a bit. Every organization wants to be data-driven. The goal is to capture data, convert it into the right insights, and integrate those insights quickly and efficiently into your business decisions and processes. And this includes the AI space.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Alation

MARCH 1, 2022

There are many approaches to manage and use data. Despite a plethora of frameworks, ideologies and best practices in the data world, data is fluid and must adapt to unique scenarios. As data complexity increases and organizations become more ‘data driven’, catalogs will continue to rank as a high priority.”.

Data Warehouse 52

Data Warehouse Data Lake Risk Data-driven 52

Alation

APRIL 14, 2022

Moving data to the cloud can bring immense operational benefits. However, the sheer volume and complexity of today’s enterprise data can cause downstream headaches for data users. Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. Data pipeline orchestration.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Modeling 76

Sisense

JULY 22, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways organizations tackle the challenges of this new world to help their companies and their customers thrive. Understanding how data becomes insights.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Alation

JUNE 9, 2021

According to a recent survey by Alation , 78% of enterprises have a strategic initiative to become more data-driven in their decision making. According to Gartner, data culture is a top priority for chief data officers (CDOs) and chief data & analytics officers (CDAOs). What is Data Search & Discovery?

Data Governance 59

Data Governance Data-driven Machine Learning Data Lake 59

Cloudera

OCTOBER 25, 2022

Enabling data and analytics in the cloud allows you to have infinite scale and unlimited possibilities to gain faster insights and make better decisions with data. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Data Processing 52

Data Processing Data Lake Cost-Benefit Risk 52

BI-Survey

NOVEMBER 23, 2021

The existence of data silos is nothing new. Data-producing applications were once isolated systems. The transactional data was stored in isolated data sets and initially served only one purpose, namely, to document the transaction that had taken place. Over time, enterprises realized that data is worth more.

Digital Transformation 52

Digital Transformation Data Warehouse Data Lake Data-driven 52

AWS Big Data

MARCH 3, 2023

In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights.

Software 52

Software Data Lake Testing Cost-Benefit 52

Domino Data Lab

JUNE 15, 2021

Over the next decade, the companies that will beat competitors will be “model-driven” businesses. These companies often undertake large data science efforts in order to shift from “data-driven” to “model-driven” operations, and to provide model-underpinned insights to the business. Why Snowflake UDFs.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Companies, both big and small, are seeking the finest ways to leverage their data into a competitive advantage.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Alation

AUGUST 4, 2022

It’s been one decade since the “ Big Data Era ” began (and to much acclaim!). Analysts asked, What if we could manage massive volumes and varieties of data? Yet the question remains: How much value have organizations derived from big data? Big Data as an Enabler of Digital Transformation.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

erwin

JULY 17, 2019

Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Constructing A Digital Transformation Strategy: Data Enablement. Many organizations prioritize data collection as part of their digital transformation strategy.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

BI-Survey

DECEMBER 22, 2020

Digitalization is on the agenda of almost every company, and data is the foundation of digitalization. Data management is unfortunately considered to be a thankless task. Data management is unfortunately considered to be a thankless task. Data experts know all too well that their company data is usually not in such good shape.

Data-driven 52

Data-driven Data Strategy Strategy Enterprise 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52